The First Generation of AI-Assisted Programming Learners: Gendered Patterns in Critical Thinking and AI Ethics of German Secondary School Students
This research addresses a gap in understanding the next generation of software engineers' critical thinking and ethical views in AI-assisted programming, with implications for culturally responsive education.
The study investigated how German secondary school students critically engage with AI-assisted programming and perceive AI ethics, finding that while students show strong ethical awareness, many use AI-generated code without fully understanding it, and gender differences exist in usage patterns and attitudes.
The first generation of students is learning to program alongside GenAI (Generative Artificial Intelligence) tools, raising questions about how young learners critically engage with them and perceive ethical responsibilities. While prior research has focused on university students or developers, little is known about secondary school novices, who represent the next cohort of software engineers. To address this gap, we conducted an exploratory study with 84 German secondary school students aged 16-19 attending software development workshops. We examined their critical thinking practices in AI-assisted programming, perceptions of AI ethics and responsibility, and gender-related differences in their views. Our results reveal an AI paradox: students demonstrate strong ethical reasoning and awareness about AI, yet many report integrating AI-generated code without a thorough understanding of it. The majority of our cohort attributed significant responsibility for AI practices to politics and corporations, potentially reflecting Germany's cultural context, with its strict regulations and data privacy discourse. Boys reported more frequent and experimental use of AI-assisted programming, whereas girls expressed greater scepticism and emphasised peer collaboration over GenAI assistance. Our findings highlight the importance of culturally responsive software engineering education that strengthens critical AI literacy in AI-assisted programming by linking ethics to concrete code artefacts and preparing young learners for this AI-driven software landscape.